• 제목/요약/키워드: Weighted Average Model

검색결과 226건 처리시간 0.02초

부분부재고를 고려한 경제적 생산량모델에 관한 연구 (A study on the economic production quantity model with partial backorders)

  • 남상진;김정자
    • 한국경영과학회지
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    • 제19권3호
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    • pp.81-91
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    • 1994
  • This paper is to build an economic production quantity model for situations, in which, during the stockout period, a fraction .betha.(backorder ratio) of the demand is backordered and remaining fraction (1-.betha.) is lost. This paper develops an objective function representing the average annual cost of a production system by defining a time-weighted backorder cost and a lost sales penalty cost per unit lost under the assumptions of deterministic demand rate and deterministic production rate, and provides an algorithm for its optimal solution. At the extreme .betha.= 1, the presented model reduces to the Fabrycky's model with complete backorders.

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다중모델적응추정방식을 이용한 강우-유출량의 실시간 예측 (Real time forecasting of rainfall-runoff using multiple model adaptive estimation)

  • 최선욱;김운해;김영철
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.24-27
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    • 1996
  • The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.

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Multivariate GARCH and Its Application to Bivariate Time Series

  • Choi, M.S.;Park, J.A.;Hwang, S.Y.
    • Journal of the Korean Data and Information Science Society
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    • 제18권4호
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    • pp.915-925
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    • 2007
  • Multivariate GARCH has been useful to model dynamic relationships between volatilities arising from each component series of multivariate time series. Methodologies including EWMA(Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model) models are comparatively reviewed for bivariate time series. In addition, these models are applied to evaluate VaR(Value at Risk) and to construct joint prediction region. To illustrate, bivariate stock prices data consisting of Samsung Electronics and LG Electronics are analysed.

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시간행동 행태을 이용한 영업용 운전자들의 이산화질소 개인 노출량 예측 (Estimation of Exposure to Nitrogen Dioxide in Professional Drivers Using Time Activity Pattern)

  • 방용남;손부순;양원호;박종안;장봉기
    • 한국환경보건학회지
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    • 제27권1호
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    • pp.20-26
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    • 2001
  • personal nitrogen dioxide(NO$_2$) exposures for 31 professional drivers were measured using passive sampler and time activity diary in Asan and Chunan area, and were estimated using time-weighted average model. Mean concentrations of driver’s indoor and outdoor were 24.7$\pm$10.7 ppb and 23.3$\pm$8.3 ppb, respectively with indoor/outdoor of 1.1. Mean personal NO$_2$ exposure was 30.3$\pm$9.7 ppb. Personal NO$_2$ exposures were strongly correlated with indoor car NO$_2$ levels ($R^2$=0.80) rather than residential indoor NO$_2$ level ($R^2$=0.55). and outdoor NO$_2$ level ($R^2$=0.50). The driver’s NO$_2$ exposure using LP-gas with 24.4$\pm$8.0 ppb were statistically different from those using diesel with 36.3$\pm$14.1 ppb(p<0.01). The effect of driver’s smoking for personal NO$_2$ exposure was not found. It was considered that the main NO$_2$in driver is transportation. Since drivers mostly spent their times in indoor and inside car, time-weighted average model could be used to estimated personal NO$_2$ exposure using time activity diary, Though we did not measure all microenvironments, the estimated personal NO$_2$ exposures with 26.9$\pm$10.2 ppb were statistically correlated with measured personal NO $_2$ exposures30.3$\pm$9.7 ppb ($R^2$=0.89). The mean and standard deviation of personal NO$_2$ exposure using Mote-Carlo simulation were 26.6$\pm$7.2 ppb.

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Hybrid receptor model을 이용한 대기 중 총 가스상 수은의 오염원 위치 추정 연구 (Identifications of Source Locations for Atmospheric Total Gaseous Mercury Using Hybrid Receptor Models)

  • 이용미;이승묵;허종배;홍지형;이석조;유철
    • 한국환경과학회지
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    • 제19권8호
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    • pp.971-981
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    • 2010
  • The objectives of this study were to measure ambient total gaseous mercury (TGM) concentrations in Seoul, to analyze the characteristics of TGM concentration, and to identify of possible source areas for TGM using back-trajectory based hybrid receptor models like PSCF (Potential Source Contribution Function) and RTWC (Residence Time Weighted Concentration). Ambient TGM concentrations were measured at the roof of Graduate School of Public Health building in Seoul for a period of January to October 2004. Average TGM concentration was $3.43{\pm}1.17\;ng/m^3$. TGM had no notable pattern according to season and meteorological phenomena such as rainfall, Asian dust, relative humidity and so on. Hybrid receptor models incorporating backward trajectories including potential source contribution function (PSCF) and residence time weighted concentration (RTWC) were performed to identify source areas of TGM. Before hybrid receptor models were applied for TGM, we analysed sensitivities of starting height for HYSPLIT model and critical value for PSCF. According to result of sensitivity analysis, trajectories were calculated an arrival height of 1000 m was used at the receptor location and PSCF was applied using average concentration as criterion value for TGM. Using PSCF and RTWC, central and eastern Chinese industrial areas and the west coast of Korea were determined as important source areas. Statistical analysis between TGM and GEIA grided emission bolsters the evidence that these models could be effective tools to identify possible source area and source contribution.

가중평균대리모델을 이용한 환기용 축류송풍기의 고효율 최적설계 (High-Efficiency Design of a Ventilation Axial-Flow Fan by Using Weighted Average Surrogate Models)

  • 김재우;김진혁;이찬;김광용
    • 대한기계학회논문집B
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    • 제35권8호
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    • pp.763-771
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    • 2011
  • 본 연구에서는 환기용 축류송풍기에 대하여 효율을 목적함수로 하는 수치최적설계를 수행하였다. 유동해석은 삼차원 Reynolds-averaged Navier-Stokes(RANS) 방정식을 통하여 이뤄졌으며, 난류모델로는 Shear Stress Transport 모델을 사용하였다. 최적설계를 위한 설계변수로는 허브비, 날개의 중간 및 팁 스팬에서의 엇갈림각을 사용하였다. 실험계획법으로 라틴하이퍼큐브 샘플링 방법을 사용하여 설계영역 내에서 25개의 실험점을 추출하였다. 최적설계기법인 가중평균대리모델과 삼차원 RANS 해석을 결합하여 수치최적설계를 수행하였으며, 가중평균대리모델로는 WTA1, WTA2 및 WTA3 모델을 사용하였다. 수치 최적설계에 의해 얻어진 최적형상들의 성능을 기준형상과 비교하였으며, 성능이 가장 좋은 모델에 대하여 기준형상과의 내부유동장 비교 및 분석을 통해 성능이 향상된 원인을 규명하였다.

Number of sampling leaves for reflectance measurement of Chinese cabbage and kale

  • Chung, Sun-Ok;Ngo, Viet-Duc;Kabir, Md. Shaha Nur;Hong, Soon-Jung;Park, Sang-Un;Kim, Sun-Ju;Park, Jong-Tae
    • 농업과학연구
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    • 제41권3호
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    • pp.169-175
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    • 2014
  • Objective of this study was to investigate effects of pre-processing method and number of sampling leaves on stability of the reflectance measurement for Chinese cabbage and kale leaves. Chinese cabbage and kale were transplanted and cultivated in a plant factory. Leaf samples of the kale and cabbage were collected at 4 weeks after transplanting of the seedlings. Spectra data were collected with an UV/VIS/NIR spectrometer in the wavelength region from 190 to 1130 nm. All leaves (mature and young leaves) were measured on 9 and 12 points in the blade part in the upper area for kale and cabbage leaves, respectively. To reduce the spectral noise, the raw spectral data were preprocessed by different methods: i) moving average, ii) Savitzky-Golay filter, iii) local regression using weighted linear least squares and a $1^{st}$ degree polynomial model (lowess), iv) local regression using weighted linear least squares and a $2^{nd}$ degree polynomial model (loess), v) a robust version of 'lowess', vi) a robust version of 'loess', with 7, 11, 15 smoothing points. Effects of number of sampling leaves were investigated by reflectance difference (RD) and cross-correlation (CC) methods. Results indicated that the contribution of the spectral data collected at 4 sampling leaves were good for both of the crops for reflectance measurement that does not change stability of measurement much. Furthermore, moving average method with 11 smoothing points was believed to provide reliable pre-processed data for further analysis.

자동차 헤드램프 부품의 경량화 사출 성형기술 및 변형 저감에 관한 연구 (A study on light weighted injection molding technology and warpage reduction for lightweight automotive head lamp parts)

  • 정의철;손정언;민성기;김종헌;이성희
    • Design & Manufacturing
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    • 제13권2호
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    • pp.1-5
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    • 2019
  • In this study, micro cellular injection molding of automobile head lamp housing with uneven thickness structure was performed to obtain improvement on deformation and light-weight of the part. The thickness of the presented model was uniformly modified to control the deformation of the molded part. In order to maximize the lightweight ratio, the model having an average thickness of 2.0 mm were thinly molded to an average thickness of 1.6 mm. GFM(Gas Free Molding) and CBM(Core Back Molding) technology were applied to improve the problems of the conventional foam molding method. Equal Heat & Cool system was also applied by 3D cooling core and individual flow control system. Warpage of the molded parts with even cooling was minimized. To improve the mechanical properties of foamed products, complex resin containing nano-filler was used and variation of mechanical properties was evaluated. It was shown that the weight reduction ratio of products with light-weighted injection molding was 8.9 % and the deformation of the products was improved from the maximum of 3.6 mm to 2.0 mm by applying Equal Heat & Cool mold cooling system. Also the mechanical strength reduction of foamed product was less than 12% at maximum.

FRM: Foundation-policy Recommendation Model to Improve the Performance of NAND Flash Memory

  • Won Ho Lee;Jun-Hyeong Choi;Jong Wook Kwak
    • 한국컴퓨터정보학회논문지
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    • 제28권8호
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    • pp.1-10
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    • 2023
  • 최근, 낸드 플래시 메모리는 비휘발성, 높은 집적도, 높은 내구성으로 인하여 다양한 컴퓨터 시스템에서 자기 디스크를 대체하고 있지만 연산 처리 속도 불균형 및 수명 제한과 같은 한계를 가진다. 따라서 낸드 플래시 메모리의 단점을 극복하고자 디스크 버퍼 관리정책들이 연구되고 있다. 비록 이러한 관리정책들이 다양한 작업 환경과 응용 프로그램의 실행 특성을 반영하는 것은 명확하나, 이들을 위한 기초 관리 정책 결정 방식에 대한 연구는 그에 비하면 미흡하다. 본 논문에서는 낸드 플래시 메모리를 효율적으로 활용하기 위한 기초 관리정책 제안 모델인 FRM을 소개한다. FRM은 워크로드를 다양한 특성에 따라 분석하고 낸드 플래시 메모리가 가지는 특성들과 조합하는 모델로, 이를 통해 작업 환경에 가장 알맞은 기초 관리 정책을 제시한다. 결과적으로 제안하는 모델은 학습 데이터와 검증 데이터에 대해 Accuracy와 Weighted Average 측면에서 각각 92.85%와 88.97%의 기초 관리정책 예측 정확도를 보여주었다.

A Comparative study on smoothing techniques for performance improvement of LSTM learning model

  • Tae-Jin, Park;Gab-Sig, Sim
    • 한국컴퓨터정보학회논문지
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    • 제28권1호
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    • pp.17-26
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    • 2023
  • 본 연구논문에서는 LSTM 기반의 학습 모델 적용과 그 효용성을 높일 수 있도록 몇 가지 평활 기법을 비교, 적용하고자 한다. 적용된 평활 기법은 Savitky-Golay, 지수 평활법, 가중치 이동 평균 등이다. 본 연구를 통해 비트코인 데이터에 LSTM모델 적용 시 보여준 결과 값보다 전처리 과정에서 적용된 Savitky-Golay 필터가 적용된 LSTM 알고리즘이 예측 성능에 유의미한 좋은 결과를 보였다. 예측 성능 결과를 확인하기 위해 비트코인 가격 예측에 따른 복잡 요인을 제거하는데 사용된 LSTM의 경우와 Savitzky-Golay LSTM 모델에 따른 학습 손실율과 검증 손실율을 비교하고 그 신뢰성을 높일 수 있도록 20회 평균값으로 실험하였다. 그 결과 (3.0556, 0.00005), (1.4659, 0.00002)의 값을 얻을 수 있었다. 결과적으로는 비트코인과 같은 암호화폐가 주식보다 더한 변동성을 가지는 만큼 데이터 전처리 과정에서 평활 기법(Savitzky-Golay)을 적용하여 잡음(Noise)을 제거하였으며, 전처리 후의 데이터는 LSTM 신경망 학습을 통해서 비트코인 예측률을 높이는데 가장 유의미한 결과를 얻을 수 있었다.